Triple
T19456206
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | RoboCop (2014 film) |
E486738
|
entity |
| Predicate | screenwriter |
P2831
|
FINISHED |
| Object | Michael Miner |
—
|
NE NERFINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Michael Miner | Statement: [RoboCop (2014 film), screenwriter, Michael Miner]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Michael Miner Context triple: [RoboCop (2014 film), screenwriter, Michael Miner]
-
A.
Michael Miner
chosen
Michael Miner is an American screenwriter best known for co-writing the influential 1987 science fiction film "RoboCop."
-
B.
Rich Miner
Rich Miner is a technology entrepreneur and investor best known as a co-founder of Android Inc. and a general partner at Google Ventures.
-
C.
Steven Miner
Steven Miner is an individual notable enough to be recognized as a namesake of the surname Miner, though specific widely known biographical details are not clearly established.
-
D.
Jan Miner
Jan Miner was an American actress best known for her long-running role as Madge the manicurist in Palmolive television commercials and for her work in radio, film, and theater.
-
E.
Samuel Mines
Samuel Mines was an American editor best known for his influential work in mid-20th-century science fiction magazines.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d8e8d86d608190bd199a98d0297f27 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e633c4088881908f23f25a82a513f6 |
completed | April 20, 2026, 2:10 p.m. |
Created at: April 10, 2026, 1:38 p.m.